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Queues, collisions and extremes of integral mean of stationary Gaussian processes

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If you have a question about this talk, please contact Mustapha Amrani.

Stochastic Processes in Communication Sciences

Let {Z(t):t>0} be a centered stationary Gaussian process with continuous sample paths a.s.

The talk will be focused on the analysis of the asymptotics of P(sup{(1/t)int_0^t Z(s)ds>u) as u->oo.

As an application of the considered problem, we will derive the exact asymptotics of

- the probability of buffer emptiness for a Gaussian fluid gueue under many-sources regime;

- the probability of a collision of differentiable Gaussian stochastic processes with stationary increments.

The talk is based on a joint work with Kamil Tabi’s.

This talk is part of the Isaac Newton Institute Seminar Series series.

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